Natural Language Web Access via Concept Parsing
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Solution Overview
Problem
Current computer systems lack the ability to understand human thought and natural language effectively, as they cannot parse complex mental concepts encoded in language expressions, limiting their ability to respond appropriately to natural language inputs.
Innovation Solution
A system utilizing a registry database and parser to associate natural language variations with web addresses, allowing users to access web pages using natural language representations, by storing associations between concepts and their variations, and using a parser to identify concepts and generate short tags for navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional computer programs process text at high level using word search and speech to text, then text processing capability is provided, but the system cannot understand the meaning incorporated in text
Solution Approach 1:
The patent introduces an intermediary layer between conventional text processing and meaning understanding. This intermediary comprises a database of mental concepts, binary operations, and language expressions that translates processed text into comprehensible meaning representations, allowing the system to bridge the gap between word-level processing and semantic understanding
Solution Approach 2:
The patent replaces the mechanical text processing system with a cognitive-inspired system that uses binary mental operations similar to human thought processes. Instead of relying solely on pattern matching and keyword search, the system substitutes a mechanism that reconstructs mental concepts and their relationships, enabling genuine meaning comprehension
2Reliability
If users must remember exact web page addresses (URLs) to access web pages, then web page access is achieved, but user convenience and ease of operation deteriorates
Solution Approach 1:
The patent creates a copy or representation of the web page address system that uses natural language instead of exact URLs. The system stores associations between natural language descriptions and web page addresses, allowing users to access pages through conceptual descriptions rather than precise URL typing, thereby maintaining access reliability while dramatically improving ease of operation
Solution Approach 2:
The patent changes the parameter of web page addressing from exact URL strings to natural language concepts. By transforming the addressing parameter from precise technical identifiers to flexible human-language descriptions, the system maintains the ability to reliably access web pages while making the interface much more user-friendly and memorable
3Adaptability or versatility
If a database stores associations between concepts and all natural language variations, then natural language accessibility is improved, but device complexity increases
Solution Approach 1:
The patent segments the complex database into distinct components: a language database storing language expressions and their associated binary mental operations, and a concept database storing mental concepts and their relationships. This segmentation allows the system to handle natural language variations systematically while managing complexity through modular organization of database elements
Data Source
AI summary
Systems and methods for building an interface that receives and responds to varied natural language expressions. In an embodiment, the system receives a natural language expression in text or audio, and translates it by building at least one data structure which reflects the concepts expressed in the natural language expression. The data structure may comprise a symbol representing each concept. In an embodiment, a parser utilizes the data structure to parse language expressions to single concept symbols that represent the meaning of the expressions. Response actions may also be performed in response to the parsed language expressions. In addition, a parser may receive a single concept symbol, and generate one or many natural language expressions of the meaning of the concept symbol. Furthermore, the system may be configured to understand the local meaning of words and phrases.